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---
license: mit
base_model: unknown
tags:
- vietnamese
- hate-speech-detection
- text-classification
- offensive-language-detection
datasets:
- visolex/vihsd
metrics:
- accuracy
- macro-f1
- weighted-f1
model-index:
- name: bilstm-hsd
results:
- task:
type: text-classification
name: Hate Speech Detection
dataset:
name: ViHSD
type: hate-speech-detection
metrics:
- type: accuracy
value: 0.8388
- type: macro-f1
value: 0.3041
- type: weighted-f1
value: 0.7652
- type: macro-precision
value: 0.2796
- type: macro-recall
value: 0.3333
---
# BILSTM: Hate Speech Detection for Vietnamese Text
This model is a fine-tuned version of [unknown](https://huggingface.co/unknown)
on the **ViHSD (Vietnamese Hate Speech Detection Dataset)** for classifying Vietnamese text into three categories: CLEAN, OFFENSIVE, and HATE.
## Model Details
* **Base Model**: unknown
* **Description**: bilstm fine-tuned for Vietnamese Hate Speech Detection
* **Architecture**: Unknown
* **Dataset**: ViHSD (Vietnamese Hate Speech Detection Dataset)
* **Fine-tuning Framework**: HuggingFace Transformers + PyTorch
* **Task**: Hate Speech Classification (3 classes)
### Hyperparameters
* **Batch size**: `32`
* **Learning rate**: `2e-5`
* **Epochs**: `100`
* **Max sequence length**: `256`
* **Weight decay**: `0.01`
* **Warmup steps**: `500`
* **Early stopping patience**: `5`
* **Optimizer**: AdamW
* **Learning rate scheduler**: Cosine with warmup
## Dataset
Model was trained on **ViHSD (Vietnamese Hate Speech Detection Dataset)** containing ~10,000 Vietnamese comments from social media.
### Label Descriptions:
* **CLEAN (0)**: Normal content without offensive language
* **OFFENSIVE (1)**: Mildly offensive or inappropriate content
* **HATE (2)**: Hate speech, extremist language, severe threats
## Evaluation Results
The model was evaluated on test set with the following metrics:
* **Accuracy**: `0.8388`
* **Macro-F1**: `0.3041`
* **Weighted-F1**: `0.7652`
* **Macro-Precision**: `0.2796`
* **Macro-Recall**: `0.3333`
### Basic Usage
```python
from transformers import AutoTokenizer, AutoModelForSequenceClassification
import torch
# Load model and tokenizer
model_name = "visolex/bilstm-hsd"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForSequenceClassification.from_pretrained(
model_name
)
# Classify text
text = "Văn bản tiếng Việt cần phân loại"
inputs = tokenizer(text, return_tensors="pt", padding=True, truncation=True)
with torch.no_grad():
outputs = model(**inputs)
predictions = torch.nn.functional.softmax(outputs.logits, dim=-1)
predicted_label = torch.argmax(predictions, dim=-1).item()
# Label mapping
label_names = {
0: "CLEAN",
1: "OFFENSIVE",
2: "HATE"
}
print(f"Predicted label: {label_names[predicted_label]}")
print(f"Confidence scores: {predictions[0].tolist()}")
```
**⚠️ Note for Vocab-based Models**: This model (`bilstm`) uses custom vocabulary-based tokenization and does not include a Hugging Face tokenizer. You will need to implement custom tokenization or load a tokenizer from a compatible base model. The model expects word-level tokenized input.
## Training Details
### Training Data
- **Dataset**: ViHSD (Vietnamese Hate Speech Detection Dataset)
- **Total samples**: ~10,000 Vietnamese comments from social media
- **Training split**: ~70%
- **Validation split**: ~15%
- **Test split**: ~15%
### Training Configuration
- **Framework**: PyTorch + HuggingFace Transformers
- **Optimizer**: AdamW
- **Learning Rate**: 2e-5
- **Batch Size**: 32
- **Max Length**: 256 tokens
- **Epochs**: 100 (with early stopping patience: 5)
- **Weight Decay**: 0.01
- **Warmup Steps**: 500
## Contact & Support
- **GitHub**: [ViSoLex Hate Speech Detection](https://github.com/visolex/hate-speech-detection)
- **Issues**: [Report Issues](https://github.com/visolex/hate-speech-detection/issues)
- **Questions**: Open a discussion on the model's Hugging Face page
## License
This model is distributed under the MIT License.
## Acknowledgments
- Base model: [unknown](https://huggingface.co/unknown)
- Dataset: ViHSD (Vietnamese Hate Speech Detection Dataset)
- Framework: [Hugging Face Transformers](https://huggingface.co/transformers)
- ViSoLex Toolkit
---
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